Design Thinking for the Greater Good Read online

  That same kind of revolutionary shift is under way today in innovation. Innovation I, the old paradigm, looks a lot like quality assurance. It is isolated in experts and senior leaders, decoupled from the everyday work of the organization. In Innovation I, innovation is about big breakthroughs done by special people. Design in the Innovation I world is mostly about aesthetics or technology.

  The shift from Innovation I to Innovation II.

  We are seeing the emergence of Innovation II, the democratizing of innovation. In this world, we are all responsible for innovation. Even the term itself has a new meaning. Innovation isn’t only—or even mostly—about big breakthroughs; it is about improving value for the stakeholders we serve. And everybody in an organization has a role to play. It is not that we no longer care about big, disruptive innovations or that we don’t still need expert innovators and designers—it is just that we acknowledge two truths: first, it is often impossible to tell early in the life of an innovation just how big or small it will someday be; and, second, many small things can add up to something big.

  As Innovation II emerges, design thinking provides a common language and problem-solving methodology (as TQM did in quality) that everyone can use to help their organization more effectively accomplish key strategic objectives, whether those objectives involve traditional business outcomes like profitability and competitive advantage or social outcomes like reducing poverty or creating jobs. As organizations develop this organization-wide capability for innovation, they will enhance their ability to achieve their objectives by generating more innovative and effective outcomes and processes that create better value for the stakeholders they serve and that make the organizations more effective in meeting their missions.

  Design thinking makes Innovation II possible by encouraging distinct shifts in mindsets and behaviors. These shifts impact the individuals, teams, and extended group of stakeholders who do the designing, the way in which they identify problems and seek solutions, and the basic nature of the conversation itself. It also involves changes in the organizational context to facilitate such work at the individual and team levels.

  In the remainder of part 1 of this book, we provide an overview of what such a change looks like and how it impacts the behavior of the specific people involved. In part 2, we share ten stories from a broad cross section of organizations, which allows us to look in depth at the different roles design thinking can play. Part 3 contains a detailed, step-by-step walk through our own design thinking methodology, illustrated with a final story about a group of educators attempting their first project, which aims to provide a blueprint of how the complete end-to-end process looks in practice. The book concludes with some thoughts about how to build an organizational infrastructure to better support the democratizing of innovation.

  As we get started, we first want to talk at a more strategic level about the differences we observe in Innovation I versus Innovation II organizations and why they matter. In the remainder of the book, we will look at how these new Innovation II mindsets and behaviors play out in innovation projects led by real people in real organizations.

  It all starts with who does the innovating.

  Who Gets to Innovate? Engaging New Voices

  The most obvious marker of the transition to an Innovation II world is the question of who is invited to innovate—in other words, who designs? In Innovation I, innovation and design are the domain of experts, policy makers, planners, and senior leaders. Everyone else is expected to step away. This perspective was vividly illustrated by a comment made to us by the chief design officer of a large global corporation, who suggested that encouraging nondesigners to practice design thinking was like encouraging those without a medical license to practice medicine.

  In Innovation II, the search for opportunities to innovate is everybody’s job, so everybody designs. Here, design is not primarily about the design of products or even user experiences; instead, design thinking is seen as a problem-solving process appropriate for use by a wide variety of people. Design tools like jobs to be done, journey mapping, visualization, and prototyping become as much a part of the manager’s tool kit as Excel spreadsheets, as much a part of a teacher’s tool kit as lesson plans, and as much a part of a nurse’s tool kit as a stethoscope. Many of the most compelling stories in this book illustrate the power of inviting a broader and more diverse set of people into the design process and demonstrate how design thinking can be used to provide a common language, method, and tool kit to make such widespread participation efficient and scalable.

  But the role of individuals isn’t the only thing that changes in the evolution from Innovation I to Innovation II. The composition of the teams driving innovation changes as well. When a group of faculty meets in isolation to design a new curriculum, you are witnessing the Innovation I end of design. These homogeneous teams of “experts” consist of people who share the same functional experience and outlook and, as a result, the same mental models. This homogeneity has the advantage of reducing friction and speeding decision making, but often at the cost of more creative solutions.

  As we move toward Innovation II, a more diverse set of voices is included. In the early stages, this inclusion often takes the form of ethnographic research rather than actual participation. Even if the room is still full of engineers, teachers, or health care professionals, they are now bringing data in from people with different perspectives.

  The role of external stakeholders also starts to shift in the path from Innovation I to Innovation II. Echoing how suppliers were treated in Quality I, in the world of Innovation I, knowledge is proprietary and relationships are instrumental: citizens are segmented by how they vote, students are vessels to be taught, patients are bodies to be healed, and subcontractors are members of the supply chain—all elements of an organization’s ecosystem that must be managed, kept at arm’s length, and informed on a need-to-know basis.

  Relationships differ in Innovation II, and co-creation and open innovation play an important role. Trusted partners are engaged. The Innovation II organization seeks strategic allies outside of its normal orbit. It seeks partners with similar intentions, who bring missing competencies to achieve a shared vision. In these partners, it seeks interests that align and capabilities that are complementary. Such external partners represent new possibilities of inventing together, rather than constraints to be managed.

  How Do They Innovate? Changing the Conversation

  As the capability for innovation spreads across the organization and its ecosystem, how the organization designs changes as well. The nature of the innovation conversation itself begins to shift, influencing both the definition of problems and opportunities at the outset and the differing expectations for the kinds of answers that emerge at the end of the process.

  We first notice the difference in the conversation around framing the problem. In Innovation I, defining the problem is rarely seen as part of the challenge, nor is the obvious definition questioned as a starting point. Problems are treated as given, as known. The focus moves quickly to the more relevant, action-oriented issue: how to solve them.

  But, much as the search for root cause became central in Quality II, attention to careful definition of a problem is seen as critical in Innovation II. Decision makers begin the process with less confidence in the correctness of their initial problem definition. The definition of the problem is a hypothesis to be tested, as are its solutions. And for effective problem framing, local intelligence is almost always critical. We will see, in many of the stories that follow, that breakthroughs come with the redefinition of the problem itself.

  As we turn to the solution space, it too will look different in Innovation II. We employ design thinking in the first place because we want better answers to our problems. But the changes we observe in the answers in Innovation II organizations go well beyond enhanced creativity. Perhaps most striking is the belief about how many answers we need to work with. In the Innovation I world, decision makers re
ally do believe that one “best” answer exists. In traditional economics, that would be the equilibrium point, the magical intersection of supply and demand. Decision makers in Innovation I even believe that they can “prove” that the answer is the correct one right at the start of the process.

  But even economists (the last academics on record who truly believe people are rational actors) are abandoning the notion that one best equilibrium point exists in today’s complex social systems, where the interactions are too complicated to predict cause and effect and where even small changes in initial conditions can yield massive changes in outcomes (the famous butterfly effect). Accordingly, in Innovation II, the search is for “better” rather than “best.” Solutions are seen as man-made inventions rather than eternal truths. Attempts to demonstrate the superiority of any single solution before its implementation give way to a preference for optionality. Multiple solutions are moved into testing because decision makers distrust their ability to predict success and believe that numerous answers are possible—and desirable. We really won’t know what works until we try it. In our stories, success results from the energy that implementers bring to particular solutions that emerge during the process. It is expected to take multiple iterations of testing and refining and to be more a result of learning than of getting it right the first time.

  In the absence of confidence in the ability to predict winners and losers, the size and scope of the ideas considered worth pursuing change as well. We have entered the land of “small bets” and “fail fast,” terms we often hear these days. But these are more than just Silicon Valley platitudes; they reflect the reality of designing effectively and efficiently in complex environments with high uncertainty. Instead of big ideas scaled quickly, basic logic tells us to start small and defer scaling any one solution until its underlying assumptions have been thoroughly vetted. It is not that Innovation II–minded organizations want ideas to stay small; they just believe in starting small.

  But nowhere is the shift between Innovation I and Innovation II in the organizations we have studied more striking than in the innovation conversation itself. In Innovation I, innovation usually begins with solution identification, as we talked about earlier. The problem with beginning here, in a complex world with diverse stakeholders, is far more serious than just missing a few creative alternatives. It colors the entire dynamic of how members of the conversation interact with each other. Because participants tend to bring solutions from their own worldviews into the conversations, it sets up immediate debates among alternatives, with advocates for competing ideas each marshaling their own supporting evidence. The definition of the problem to start with, the alignment on assumptions, and even the generation of the ideas themselves are taken almost for granted. The emphasis is on evaluation and selection. And if participants bring the kind of diversity to the conversation that we have said leads to more creativity in theory, this same diversity of worldviews often will drag them down a path of conflict in reality.

  In Innovation II, the focus is on developing previously unseen possibilities rather than starting with existing identifiable options. A significant investment is made in the exploration of existing conditions as a precondition to the generation of ideas; the extensive use of ethnography is meant to make the idea generation process more user driven and data driven. In the design thinking methodology, the pursuit of insights precedes the pursuit of solutions. Insights about the needs of those we are designing for—and the subsequent design criteria these insights spawn—are the heart of user-driven idea generation.

  The only way to turn theoretical diversity into actual creativity is to change the nature of the conversation itself to incorporate an increasing role for dialogue as well as debate, for inquiry as well as advocacy. We need to learn to listen to understand rather than to argue, to listen for possibilities rather than for weaknesses. Design thinking’s tools for collaborative problem solving can assist in the search for higher-order solutions by offering a structured process in which that dialogue and inquiry occurs, and where divergent views are surfaced and explored, rather than relying solely on the skills of the leader of the conversation.

  Where Do They Innovate? Changing the Organization

  To move from Innovation I to II, it is not only people and processes that have to change. Organizations will need to create a context in which doing things differently makes sense and feels safe. They will need to acknowledge the reality of messy problems, cultivate variance rather than driving it out, and help people choose action over inaction.

  Acknowledging the Reality of Messy Problems

  Among the qualities of Innovation I organizations that stymie the shift to Innovation II, none is more obvious in our research than discomfort with ambiguity and messiness. Innovation II requires a willingness to wallow in the data—to struggle with ambiguous problem definitions, search for better insights, and sometimes get it wrong. Design thinking offers a structured process and tools that acknowledge this reality. In fact, a prime source of design thinking’s distinctive contribution, under conditions of uncertainty, is its refusal to presume that clarity exists when ambiguity is tangible, to tidy up when messiness is what reality offers, or to pursue an illusory efficiency based on measures of things easily counted. Design thinking insists on recognizing the likelihood of failure, which can only be reduced, not eliminated. Many design thinking tools and steps, we have noted, address how to manage and minimize risk. Challenging organizational norms can be unsettling in mature organizations that expect perfection and fear chaos. The need for clarity and closure is embedded in most organizations, but to move toward an Innovation II operation, they must reward the courage to step into messiness, and give people the tools to do so intelligently.

  CREATING A BIAS FOR ACTION

  David Edinger, the city of Denver’s chief performance officer, works with the support of Mayor Michael Hancock to battle the “cost of hesitation,” as he calls it: the tendency of staff to fall back onto what they are used to, “their habit of compliance, not performance.” The city of Denver launched its Peak Academy, an initiative to create an action bias at every level of the organization, in 2011. The academy offers training in innovation and Lean methodologies for interested employees, asking in return only that they identify and actually try something specific to improve performance in their work areas. Peak is not asking for ideas; it is requiring action. Denver’s assurance that no employee will lose a job over efficiency gains provides staff with the emotional security to risk creativity.

  After seeing the successful results in Human Services—food stamp processing time decreased from sixteen days to overnight, with no layoffs involved—other employees began to take notice. “We never advise employees to slow down,” David says. “We measure success by the number of innovations that occur, even saving nine cents in paper clips. But each team has to begin iterating something.” Reviews at thirty, sixty, and ninety days lead to better performance or to abandonment of the new concept. Either outcome is acceptable. At any point, the employees who designed the innovation are completely free to veto their own project.

  “We want the employee to take a chance, and we don’t care if it results in anything, or even if it’s very small,” David explained. “Just doing what I did yesterday has a very strong gravitational pull to it. Unless there’s someone near them, to inspire, it’s very easy to fall back into daily work mode and never actually make the jump to continuous improvement. We reinforce the notion that everyone is capable of innovating.”

  Cultivating Variance

  Mature organizations are designed for control and predictability; their aim is usually to standardize and drive out variance. Yet innovation requires willingly inducing variance and tolerating the ambiguity, lack of control, and seeming inefficiency that result. Variance may be the mother of waste, as W. Edwards Deming noted, but it is also the mother of invention. Cultivating variance on the design team helps us bring a more creative perspective to problem definition
, get more insights out of our research, and uncover solid design criteria. Cultivating variance in our design solutions fosters experimentation and gives staff the ability to place small bets fast and to iterate from the resulting learning. This level of ambiguity—and the attendant fear of the chaos of too many opinions—can be profoundly unsettling in traditional bureaucratic settings. Design thinking’s role is to reduce this discomfort and create confidence that increasing diversity in the discussion will translate into better solutions.

  Helping Staff Choose Action

  This need for order and predictability is not just organizational; it is also deeply embedded in many human individual psyches. Psychologists have demonstrated that many of the choices we make are driven primarily by a fear of making mistakes; thus, we prefer inaction to action when any choice risks failure (more on this in chapter 2). In the face of this normal human response, significant psychological safety is necessary to encourage individuals to choose action over inaction. Making it safe to take action in the face of uncertainty requires senior leaders’ support. Even in organizations where senior leadership is committed to creating a culture that tolerates mistakes and learns through iteration, many employees will find the change difficult.

  As the appetite for the design thinking tool kit and methodology spreads, the challenge for the organization shifts from encouraging and enabling people to try it to scaling it. In order for everyone to design, everyone needs to achieve literacy in design thinking, a significant challenge for people raised in an analytic world. But scaling involves more than providing training. It requires the development of other structures and resources: decision autonomy to conduct experiments, access to stakeholders for study and co-creation, and a culture willing to manage risk instead of avoiding it. It also involves the creation of an infrastructure to guide the process, and a willingness to rethink what we measure and how.